1. Field of the Invention
The present invention relates to a system for computing machine parameters, more particularly to a system for computing machine parameters of an induction machine.
2. Description of the Related Art
Nowadays, induction machines are relatively popular and are commonly applied to generators used in the industry due to simplicity and easy of operation thereof. It is important to establish an equivalent model (such as a transient model, or a steady-state model) of an induction machine for predicting performance and designing control schemes. Techniques for acquiring relevant parameters of the equivalent model of the induction machine can be generally classified into online and offline identification systems. In offline identification, the relevant parameters of the equivalent model can be found by standard tests, such as a locked rotor test, a no-load test, and a stand-still frequency response test.
In online identification, a spectrum method is used for estimating the relevant parameters of the equivalent model via features of the induction machine. A model reference adaptive system utilizes an error between estimated and reference measurements to calculate the relevant parameters. An artificial intelligence method utilizes an artificial neural network model instead of the model used in the model reference adaptive system.
The above-mentioned methods have respective advantages. However, all the methods have a general disadvantage in that all the relevant parameters can be acquired only after a rotor speed of the induction machine reaches a steady state. For example, regarding the model reference adaptive system, while circuit parameters can be obtained in an activation stage of the induction machine, mechanical parameters can be obtained only after a predetermined duration when the induction machine is in the steady state.